Multi-objective optimization of constrained parallel hybrid electric vehicle based on SPEA2

doi:10.3724/SP.J.1087.2011.03091

Journal of Computer Applications ›› 2011, Vol. 31 ›› Issue (11): 3091-3093.DOI: 10.3724/SP.J.1087.2011.03091

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Multi-objective optimization of constrained parallel hybrid electric vehicle based on SPEA2

YU Xin-bao¹,LI Shao-bo²,³,YANG Guan-ci³,QU Jing-lei²,ZHONG Yong³

1. College of Computer Science and Information, Guizhou University, Guiyang Guizhou 550003, China
2. Key Laboratory of Advanced Manufacturing Technology, Ministry of Education, Guizhou University, Guiyang Guizhou 550003, China
3. Chengdu Institute of Computer Application, Chinese Academy of Sciences, Chengdu Sichuan 610041, China

Received:2011-05-17 Revised:2011-07-03 Online:2011-11-16 Published:2011-11-01
Contact: YANG Guan-ci

基于强度Pareto进化算法的有约束并联混合动力汽车多目标优化

于新宝¹,李少波²,³,杨观赐³,璩晶磊²,钟勇³

1. 贵州大学计算机科学与信息学院, 贵阳 550003
2. 贵州大学教育部现代制造技术重点实验室, 贵阳 550003
3. 中国科学院成都计算机应用研究所, 成都 610041

通讯作者: 杨观赐
作者简介:于新宝(1985-),男,山东潍坊人,硕士研究生,主要研究方向：复杂系统多目标优化；李少波(1973-),男,湖南岳阳人,教授,博士生导师，主要研究方向：智能系统、计算智能、进化多目标优化；杨观赐(1983-),男,湖南嘉禾人,博士研究生,主要研究方向：计算智能；璩晶磊(1988-),男,河南新乡人,硕士研究生,主要研究方向：复杂系统多目标优化；钟勇(1966-),男, 研究员，博士生导师,主要研究方向：软件过程技术。
基金资助:
教育部新世纪优秀人才支持计划项目;国家863计划项目;贵州省科学技术基金资助项目

Abstract

Abstract: Weight coefficients should be employed to transform multi-objective problem of hybrid system into a single objective one. In order to avoid setting weight coefficients, a methodological approach based on Strength Pareto Evolutionary Algorithm (SPEA2) was proposed to optimize parameters of constrained Parallel Hybrid Electric Vehicle (PHEV).The Pareto dominance principle was employed to judge candidate solutions and the objective was to minimum fuel consumption and exhaust emissions while ADVISOR was used to simulate the PHEV driving. The optimal results demonstrate that adopting the methodological approach proposed in this paper to optimize parameters of power control strategy and drivetrain has a significant effect on enhancing working efficiency, promoting vehicle performance, decreasing fuel consumption and reducing exhaust emissions of PHEV.

Key words: constrained optimization, multi-objective evolutionary algorithm, hybrid electrical vehicles

摘要： 将混合动力系统多目标优化问题转化为单目标优化问题进行求解需要设置权系数。为避免设置权系数,研究基于强度Pareto进化算法（SPEA2）的有约束并联式混合动力电动汽车(PHEV)参数优化方法。该方法基于Pareto支配性原理判定候选方案的优劣,采用ADVISOR仿真PHEV，并将仿真所得的燃油消耗量与污染物排量作为候选方案的目标值。实验结果表明,该方法所获得的控制策略与传动系统参数,在提高PHEV工作效率、整车性能及降低燃油消耗与污染物排放等方面效果显著。

关键词: 带约束优化, 多目标进化算法, 混合动力汽车

CLC Number:

U469.72

YU Xin-bao LI Shao-bo YANG Guan-ci QU Jing-lei ZHONG Yong. Multi-objective optimization of constrained parallel hybrid electric vehicle based on SPEA2[J]. Journal of Computer Applications, 2011, 31(11): 3091-3093.

于新宝李少波杨观赐璩晶磊钟勇. 基于强度Pareto进化算法的有约束并联混合动力汽车多目标优化[J]. 计算机应用, 2011, 31(11): 3091-3093.

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Multi-objective optimization of constrained parallel hybrid electric vehicle based on SPEA2

基于强度Pareto进化算法的有约束并联混合动力汽车多目标优化

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